Search form

Abstract—When people work together to analyze a data set, they need to organize their findings, hypotheses, and evidence, share
that information with their collaborators, and coordinate activities amongst team members. Sharing externalizations (recorded information
such as notes) could increase awareness and assist with team communication and coordination. However, we currently know
little about how to provide tool support for this sort of sharing. We explore how linked common work (LCW) can be employed within
a ‘collaborative thinking space’, to facilitate synchronous collaborative sensemaking activities in Visual Analytics (VA). Collaborative
thinking spaces provide an environment for analysts to record, organize, share and connect externalizations. Our tool, CLIP, extends
earlier thinking spaces by integrating LCW features that reveal relationships between collaborators’ findings. We conducted a user
study comparing CLIP to a baseline version without LCW. Results demonstrated that LCW significantly improved analytic outcomes
at a collaborative intelligence task. Groups using CLIP were also able to more effectively coordinate their work, and held more discussion
of their findings and hypotheses. LCW enabled them to maintain awareness of each other’s activities and findings and link
those findings to their own work, preventing disruptive oral awareness notifications.